cuml::genetic::param Struct Reference

contains all the hyper-parameters for training More...

#include <common.h>

Collaboration diagram for cuml::genetic::param:

Public Member Functions
float	p_reproduce () const
int	max_programs () const
int	criterion () const

Public Attributes
int	population_size = 1000
int	hall_of_fame = 100
int	n_components = 10
int	generations = 20
int	tournament_size = 20
float	stopping_criteria = 0.0f
float	const_range [2] = {-1.0f, 1.0f}
int	init_depth [2] = {2, 6}
init_method_t	init_method = init_method_t::half_and_half
std::vector< node::type >	function_set
std::map< int, std::vector< node::type > >	arity_set
transformer_t	transformer = transformer_t::sigmoid
metric_t	metric = metric_t::mae
float	parsimony_coefficient = 0.001f
float	p_crossover = 0.9f
float	p_subtree_mutation = 0.01f
float	p_hoist_mutation = 0.01f
float	p_point_mutation = 0.01f
float	p_point_replace = 0.05f
float	max_samples = 1.0f
float	terminalRatio = 0.0f
std::vector< std::string >	feature_names
int	num_features
uint64_t	random_state = 0UL
int	num_epochs = 0
bool	low_memory = false

Detailed Description

contains all the hyper-parameters for training

Note

Unless otherwise mentioned, all the parameters below are applicable to all of classification, regression and transformation.

Member Function Documentation

criterion()

int cuml::genetic::param::criterion

(

)

const

criterion for scoring based on metric used

max_programs()

int cuml::genetic::param::max_programs

(

)

const

maximum possible number of programs

p_reproduce()

float cuml::genetic::param::p_reproduce

(

)

const

Computes the probability of 'reproduction'

Member Data Documentation

arity_set

std::map<int, std::vector<node::type> > cuml::genetic::param::arity_set

Initial value:

{
    {2, {node::type::add, node::type::mul, node::type::div, node::type::sub}}}

map of functions ordered by their arity

const_range

float cuml::genetic::param::const_range[2] = {-1.0f, 1.0f}

minimum/maximum value for constant nodes

feature_names

std::vector<std::string> cuml::genetic::param::feature_names

list of feature names for generating syntax trees from the programs

function_set

std::vector<node::type> cuml::genetic::param::function_set

Initial value:

{
    node::type::add, node::type::mul, node::type::div, node::type::sub}

list of functions to choose from

generations

int cuml::genetic::param::generations = 20

number of generations to evolve

hall_of_fame

int cuml::genetic::param::hall_of_fame = 100

number of fittest programs to compare during correlation (transformation-only)

init_depth

int cuml::genetic::param::init_depth[2] = {2, 6}

minimum/maximum depth of programs after initialization

init_method

init_method_t cuml::genetic::param::init_method = init_method_t::half_and_half

initialization method

low_memory

bool cuml::genetic::param::low_memory = false

Low memory flag for program history

max_samples

float cuml::genetic::param::max_samples = 1.0f

subsampling factor

metric

metric_t cuml::genetic::param::metric = metric_t::mae

fitness metric

n_components

int cuml::genetic::param::n_components = 10

number of fittest programs to return from hall_of_fame top programs (transformation-only)

num_epochs

int cuml::genetic::param::num_epochs = 0

Number of epochs for which the algorithm ran

num_features

int cuml::genetic::param::num_features

number of features in current dataset

p_crossover

float cuml::genetic::param::p_crossover = 0.9f

crossover mutation probability of the tournament winner

p_hoist_mutation

float cuml::genetic::param::p_hoist_mutation = 0.01f

hoist mutation probability of the tournament winner

p_point_mutation

float cuml::genetic::param::p_point_mutation = 0.01f

point mutation probabiilty of the tournament winner

p_point_replace

float cuml::genetic::param::p_point_replace = 0.05f

point replace probabiility for point mutations

p_subtree_mutation

float cuml::genetic::param::p_subtree_mutation = 0.01f

subtree mutation probability of the tournament winner

parsimony_coefficient

float cuml::genetic::param::parsimony_coefficient = 0.001f

penalization factor for large programs

population_size

int cuml::genetic::param::population_size = 1000

number of programs in each generation

random_state

uint64_t cuml::genetic::param::random_state = 0UL

Todo:

: feature_names

: verbose

random seed used for RNG

stopping_criteria

float cuml::genetic::param::stopping_criteria = 0.0f

metric threshold used for early stopping

terminalRatio

float cuml::genetic::param::terminalRatio = 0.0f

Terminal ratio for node selection during grow initialization. 0 -> auto-selection

tournament_size

int cuml::genetic::param::tournament_size = 20

number of programs that compete in the tournament to become part of next generation

transformer

transformer_t cuml::genetic::param::transformer = transformer_t::sigmoid

transformation function to class probabilities (classification-only)

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The documentation for this struct was generated from the following file:

• include/cuml/genetic/common.h